Overview

Dataset statistics

Number of variables14
Number of observations2968
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory347.8 KiB
Average record size in memory120.0 B

Variable types

Numeric14

Alerts

avg_basket_size is highly overall correlated with avg_ticket and 3 other fieldsHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
delta_buy_return is highly overall correlated with avg_basket_size and 5 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 5 other fieldsHigh correlation
items_purchased is highly overall correlated with avg_basket_size and 5 other fieldsHigh correlation
monetary_returns is highly overall correlated with number_returnsHigh correlation
number_returns is highly overall correlated with monetary_returnsHigh correlation
purchases is highly overall correlated with delta_buy_return and 4 other fieldsHigh correlation
recency_days is highly overall correlated with purchasesHigh correlation
unique_avg_basket is highly overall correlated with unique_products_purchasedHigh correlation
unique_products_purchased is highly overall correlated with delta_buy_return and 4 other fieldsHigh correlation
frequency is highly skewed (γ1 = 24.87687084)Skewed
monetary_returns is highly skewed (γ1 = 25.6851608)Skewed
customer_id has unique valuesUnique
recency_days has 33 (1.1%) zerosZeros
number_returns has 1481 (49.9%) zerosZeros
monetary_returns has 1481 (49.9%) zerosZeros

Reproduction

Analysis started2024-01-26 13:27:14.486485
Analysis finished2024-01-26 13:27:48.616574
Duration34.13 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

UNIQUE 

Distinct2968
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15270.377
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:48.749169image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12619.35
Q113798.75
median15220.5
Q316768.5
95-th percentile17964.65
Maximum18287
Range5940
Interquartile range (IQR)2969.75

Descriptive statistics

Standard deviation1719.1445
Coefficient of variation (CV)0.11258036
Kurtosis-1.2061782
Mean15270.377
Median Absolute Deviation (MAD)1489
Skewness0.032193711
Sum45322479
Variance2955457.9
MonotonicityNot monotonic
2024-01-26T10:27:48.977759image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17850 1
 
< 0.1%
12670 1
 
< 0.1%
17734 1
 
< 0.1%
14905 1
 
< 0.1%
16103 1
 
< 0.1%
14626 1
 
< 0.1%
14868 1
 
< 0.1%
18246 1
 
< 0.1%
17115 1
 
< 0.1%
16611 1
 
< 0.1%
Other values (2958) 2958
99.7%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18277 1
< 0.1%
18276 1
< 0.1%
18274 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18269 1
< 0.1%

gross_revenue
Real number (ℝ)

HIGH CORRELATION 

Distinct2953
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2693.4851
Minimum6.2
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:49.179754image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile229.7325
Q1570.845
median1085.51
Q32306.905
95-th percentile7169.562
Maximum279138.02
Range279131.82
Interquartile range (IQR)1736.06

Descriptive statistics

Standard deviation10135.465
Coefficient of variation (CV)3.7629558
Kurtosis397.30132
Mean2693.4851
Median Absolute Deviation (MAD)670.84
Skewness17.635372
Sum7994263.7
Variance1.0272766 × 108
MonotonicityNot monotonic
2024-01-26T10:27:49.387108image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1078.96 2
 
0.1%
2053.02 2
 
0.1%
331 2
 
0.1%
1353.74 2
 
0.1%
889.93 2
 
0.1%
745.06 2
 
0.1%
379.65 2
 
0.1%
2092.32 2
 
0.1%
731.9 2
 
0.1%
734.94 2
 
0.1%
Other values (2943) 2948
99.3%
ValueCountFrequency (%)
6.2 1
< 0.1%
13.3 1
< 0.1%
15 1
< 0.1%
36.56 1
< 0.1%
45 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
140450.72 1
< 0.1%
124564.53 1
< 0.1%
117379.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%
65039.62 1
< 0.1%

recency_days
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct272
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.309299
Minimum0
Maximum373
Zeros33
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:49.588607image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median31
Q381
95-th percentile242
Maximum373
Range373
Interquartile range (IQR)70

Descriptive statistics

Standard deviation77.760922
Coefficient of variation (CV)1.2091707
Kurtosis2.7765172
Mean64.309299
Median Absolute Deviation (MAD)26
Skewness1.7980529
Sum190870
Variance6046.7611
MonotonicityNot monotonic
2024-01-26T10:27:49.806749image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.3%
4 87
 
2.9%
2 85
 
2.9%
3 85
 
2.9%
8 76
 
2.6%
10 67
 
2.3%
9 66
 
2.2%
7 66
 
2.2%
17 64
 
2.2%
16 55
 
1.9%
Other values (262) 2218
74.7%
ValueCountFrequency (%)
0 33
 
1.1%
1 99
3.3%
2 85
2.9%
3 85
2.9%
4 87
2.9%
5 43
1.4%
7 66
2.2%
8 76
2.6%
9 66
2.2%
10 67
2.3%
ValueCountFrequency (%)
373 2
0.1%
372 4
0.1%
371 1
 
< 0.1%
368 1
 
< 0.1%
366 4
0.1%
365 2
0.1%
364 1
 
< 0.1%
360 1
 
< 0.1%
359 1
 
< 0.1%
358 4
0.1%

purchases
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7243935
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:50.019688image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile17
Maximum206
Range205
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.8577599
Coefficient of variation (CV)1.5473709
Kurtosis190.78624
Mean5.7243935
Median Absolute Deviation (MAD)2
Skewness10.765555
Sum16990
Variance78.45991
MonotonicityNot monotonic
2024-01-26T10:27:50.226237image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 784
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
1 190
 
6.4%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
Other values (46) 332
11.2%
ValueCountFrequency (%)
1 190
 
6.4%
2 784
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

unique_products_purchased
Real number (ℝ)

HIGH CORRELATION 

Distinct468
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.76449
Minimum1
Maximum7838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:50.426999image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q129
median67
Q3135
95-th percentile382
Maximum7838
Range7837
Interquartile range (IQR)106

Descriptive statistics

Standard deviation269.93294
Coefficient of variation (CV)2.1987868
Kurtosis354.77884
Mean122.76449
Median Absolute Deviation (MAD)44
Skewness15.706135
Sum364365
Variance72863.79
MonotonicityNot monotonic
2024-01-26T10:27:50.646973image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 43
 
1.4%
20 37
 
1.2%
35 35
 
1.2%
29 35
 
1.2%
19 34
 
1.1%
15 33
 
1.1%
11 32
 
1.1%
26 31
 
1.0%
27 30
 
1.0%
25 30
 
1.0%
Other values (458) 2628
88.5%
ValueCountFrequency (%)
1 6
 
0.2%
2 14
0.5%
3 15
0.5%
4 17
0.6%
5 26
0.9%
6 29
1.0%
7 18
0.6%
8 19
0.6%
9 26
0.9%
10 28
0.9%
ValueCountFrequency (%)
7838 1
< 0.1%
5673 1
< 0.1%
5095 1
< 0.1%
4580 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1637 1
< 0.1%

items_purchased
Real number (ℝ)

HIGH CORRELATION 

Distinct1670
Distinct (%)56.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1582.1044
Minimum1
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:50.884613image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile102.35
Q1296
median640
Q31399.5
95-th percentile4403.25
Maximum196844
Range196843
Interquartile range (IQR)1103.5

Descriptive statistics

Standard deviation5705.2914
Coefficient of variation (CV)3.6061408
Kurtosis516.7418
Mean1582.1044
Median Absolute Deviation (MAD)421
Skewness18.737654
Sum4695686
Variance32550350
MonotonicityNot monotonic
2024-01-26T10:27:51.430927image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 11
 
0.4%
150 9
 
0.3%
88 9
 
0.3%
246 8
 
0.3%
272 8
 
0.3%
84 8
 
0.3%
260 8
 
0.3%
288 8
 
0.3%
1200 7
 
0.2%
516 7
 
0.2%
Other values (1660) 2885
97.2%
ValueCountFrequency (%)
1 1
< 0.1%
2 2
0.1%
12 2
0.1%
16 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
23 1
< 0.1%
25 1
< 0.1%
ValueCountFrequency (%)
196844 1
< 0.1%
80263 1
< 0.1%
77373 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
63312 1
< 0.1%
58343 1
< 0.1%
57885 1
< 0.1%
50255 1
< 0.1%

avg_ticket
Real number (ℝ)

HIGH CORRELATION 

Distinct2956
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean393.16954
Minimum6.2
Maximum14844.767
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:51.655363image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile106.68475
Q1195.24339
median305.444
Q3442.63
95-th percentile919.0825
Maximum14844.767
Range14838.567
Interquartile range (IQR)247.38661

Descriptive statistics

Standard deviation489.2179
Coefficient of variation (CV)1.2442925
Kurtosis310.35682
Mean393.16954
Median Absolute Deviation (MAD)117.18067
Skewness13.261822
Sum1166927.2
Variance239334.16
MonotonicityNot monotonic
2024-01-26T10:27:51.869522image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
339.72 2
 
0.1%
512.72 2
 
0.1%
200.95 2
 
0.1%
189.825 2
 
0.1%
186.265 2
 
0.1%
394.5 2
 
0.1%
230.74 2
 
0.1%
145.525 2
 
0.1%
110.3333333 2
 
0.1%
162.6075 2
 
0.1%
Other values (2946) 2948
99.3%
ValueCountFrequency (%)
6.2 1
< 0.1%
9.14 1
< 0.1%
11.67 1
< 0.1%
13.3 1
< 0.1%
15 1
< 0.1%
20.81 1
< 0.1%
26 1
< 0.1%
26.1 1
< 0.1%
28.21666667 1
< 0.1%
28.73142857 1
< 0.1%
ValueCountFrequency (%)
14844.76667 1
< 0.1%
9341.26 1
< 0.1%
6228.2265 1
< 0.1%
4327.621667 1
< 0.1%
4279.71 1
< 0.1%
4229.365 1
< 0.1%
3914.945 1
< 0.1%
3883.985385 1
< 0.1%
3876.916944 1
< 0.1%
3690.89 1
< 0.1%

avg_recency_days
Real number (ℝ)

HIGH CORRELATION 

Distinct1258
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.302133
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:52.094485image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q125.917308
median48.267857
Q385.333333
95-th percentile200.65
Maximum366
Range365
Interquartile range (IQR)59.416026

Descriptive statistics

Standard deviation63.505358
Coefficient of variation (CV)0.94358612
Kurtosis4.9080488
Mean67.302133
Median Absolute Deviation (MAD)26.267857
Skewness2.066084
Sum199752.73
Variance4032.9306
MonotonicityNot monotonic
2024-01-26T10:27:52.301114image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 25
 
0.8%
4 22
 
0.7%
70 21
 
0.7%
7 20
 
0.7%
35 19
 
0.6%
49 18
 
0.6%
11 17
 
0.6%
46 17
 
0.6%
21 17
 
0.6%
28 16
 
0.5%
Other values (1248) 2776
93.5%
ValueCountFrequency (%)
1 16
0.5%
1.5 1
 
< 0.1%
2 13
0.4%
2.5 1
 
< 0.1%
2.601398601 1
 
< 0.1%
3 15
0.5%
3.321428571 1
 
< 0.1%
3.330357143 1
 
< 0.1%
3.5 2
 
0.1%
4 22
0.7%
ValueCountFrequency (%)
366 1
 
< 0.1%
365 1
 
< 0.1%
363 1
 
< 0.1%
362 1
 
< 0.1%
357 2
0.1%
356 1
 
< 0.1%
355 2
0.1%
352 1
 
< 0.1%
351 2
0.1%
350 3
0.1%

frequency
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1225
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.11383237
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:52.519007image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0088935048
Q10.016339869
median0.025898352
Q30.049478583
95-th percentile1
Maximum17
Range16.99455
Interquartile range (IQR)0.033138713

Descriptive statistics

Standard deviation0.40822056
Coefficient of variation (CV)3.5861552
Kurtosis989.06632
Mean0.11383237
Median Absolute Deviation (MAD)0.012196886
Skewness24.876871
Sum337.85449
Variance0.16664402
MonotonicityNot monotonic
2024-01-26T10:27:52.735366image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 198
 
6.7%
0.0625 18
 
0.6%
0.02777777778 17
 
0.6%
0.02380952381 16
 
0.5%
0.09090909091 15
 
0.5%
0.08333333333 15
 
0.5%
0.03448275862 14
 
0.5%
0.02941176471 14
 
0.5%
0.03571428571 13
 
0.4%
0.07692307692 13
 
0.4%
Other values (1215) 2635
88.8%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
3 1
 
< 0.1%
2 6
 
0.2%
1.142857143 1
 
< 0.1%
1 198
6.7%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5335120643 1
 
< 0.1%
0.5 3
 
0.1%

number_returns
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1229784
Minimum0
Maximum45
Zeros1481
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:52.938880image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile4
Maximum45
Range45
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.2974109
Coefficient of variation (CV)2.0458192
Kurtosis114.43709
Mean1.1229784
Median Absolute Deviation (MAD)1
Skewness8.0232009
Sum3333
Variance5.2780967
MonotonicityNot monotonic
2024-01-26T10:27:53.136678image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 1481
49.9%
1 832
28.0%
2 289
 
9.7%
3 140
 
4.7%
4 92
 
3.1%
5 37
 
1.2%
6 32
 
1.1%
7 21
 
0.7%
9 8
 
0.3%
11 5
 
0.2%
Other values (13) 31
 
1.0%
ValueCountFrequency (%)
0 1481
49.9%
1 832
28.0%
2 289
 
9.7%
3 140
 
4.7%
4 92
 
3.1%
5 37
 
1.2%
6 32
 
1.1%
7 21
 
0.7%
8 5
 
0.2%
9 8
 
0.3%
ValueCountFrequency (%)
45 1
 
< 0.1%
44 1
 
< 0.1%
35 1
 
< 0.1%
27 1
 
< 0.1%
21 1
 
< 0.1%
18 2
 
0.1%
17 1
 
< 0.1%
15 2
 
0.1%
14 1
 
< 0.1%
13 5
0.2%

monetary_returns
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1076
Distinct (%)36.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.704252
Minimum0
Maximum22998.4
Zeros1481
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:53.324319image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.8
Q330
95-th percentile226.875
Maximum22998.4
Range22998.4
Interquartile range (IQR)30

Descriptive statistics

Standard deviation605.35101
Coefficient of variation (CV)7.9962617
Kurtosis833.77391
Mean75.704252
Median Absolute Deviation (MAD)0.8
Skewness25.685161
Sum224690.22
Variance366449.85
MonotonicityNot monotonic
2024-01-26T10:27:53.549453image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
49.9%
4.95 19
 
0.6%
9.95 17
 
0.6%
12.75 17
 
0.6%
15 16
 
0.5%
5.9 12
 
0.4%
25.5 10
 
0.3%
4.25 10
 
0.3%
3.75 9
 
0.3%
19.9 8
 
0.3%
Other values (1066) 1369
46.1%
ValueCountFrequency (%)
0 1481
49.9%
0.42 2
 
0.1%
0.65 1
 
< 0.1%
0.95 1
 
< 0.1%
1.25 4
 
0.1%
1.45 4
 
0.1%
1.64 1
 
< 0.1%
1.65 5
 
0.2%
1.7 2
 
0.1%
1.79 1
 
< 0.1%
ValueCountFrequency (%)
22998.4 1
< 0.1%
14688.24 1
< 0.1%
8511.15 1
< 0.1%
7443.59 1
< 0.1%
5228.4 1
< 0.1%
4815.26 1
< 0.1%
4814.74 1
< 0.1%
4486.24 1
< 0.1%
4429 1
< 0.1%
3677.15 1
< 0.1%

avg_basket_size
Real number (ℝ)

HIGH CORRELATION 

Distinct1978
Distinct (%)66.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean236.25289
Minimum1
Maximum6009.3333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:53.751623image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44
Q1103.2375
median172.29167
Q3281.54808
95-th percentile599.58
Maximum6009.3333
Range6008.3333
Interquartile range (IQR)178.31058

Descriptive statistics

Standard deviation283.8932
Coefficient of variation (CV)1.2016496
Kurtosis102.78169
Mean236.25289
Median Absolute Deviation (MAD)83.041667
Skewness7.7018777
Sum701198.57
Variance80595.347
MonotonicityNot monotonic
2024-01-26T10:27:53.958905image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
114 10
 
0.3%
82 9
 
0.3%
86 9
 
0.3%
73 9
 
0.3%
136 8
 
0.3%
75 8
 
0.3%
60 8
 
0.3%
88 8
 
0.3%
130 7
 
0.2%
Other values (1968) 2881
97.1%
ValueCountFrequency (%)
1 2
0.1%
2 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
6009.333333 1
< 0.1%
4282 1
< 0.1%
3906 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2801 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%
2082.225806 1
< 0.1%

unique_avg_basket
Real number (ℝ)

HIGH CORRELATION 

Distinct1005
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.161667
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-01-26T10:27:54.166841image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.4021531
Q110
median17.2
Q327.75
95-th percentile56.9475
Maximum299.70588
Range298.70588
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation19.511925
Coefficient of variation (CV)0.88043576
Kurtosis27.710745
Mean22.161667
Median Absolute Deviation (MAD)8.2
Skewness3.5001795
Sum65775.829
Variance380.7152
MonotonicityNot monotonic
2024-01-26T10:27:54.370690image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 53
 
1.8%
14 39
 
1.3%
11 38
 
1.3%
20 33
 
1.1%
9 33
 
1.1%
1 32
 
1.1%
17 31
 
1.0%
18 30
 
1.0%
10 30
 
1.0%
5 29
 
1.0%
Other values (995) 2620
88.3%
ValueCountFrequency (%)
1 32
1.1%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
0.1%
1.5 7
 
0.2%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 24
0.8%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
259 1
< 0.1%
203.5 1
< 0.1%
148 1
< 0.1%
145 1
< 0.1%
136.125 1
< 0.1%
135.5 1
< 0.1%
127 1
< 0.1%
122 1
< 0.1%
118 1
< 0.1%

delta_buy_return
Real number (ℝ)

HIGH CORRELATION 

Distinct2951
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2617.7808
Minimum-796.86
Maximum278778.02
Zeros8
Zeros (%)0.3%
Negative3
Negative (%)0.1%
Memory size46.4 KiB
2024-01-26T10:27:54.585807image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum-796.86
5-th percentile213.114
Q1552.3125
median1055.04
Q32265.4025
95-th percentile7018.2475
Maximum278778.02
Range279574.88
Interquartile range (IQR)1713.09

Descriptive statistics

Standard deviation9929.1953
Coefficient of variation (CV)3.7929819
Kurtosis421.91006
Mean2617.7808
Median Absolute Deviation (MAD)656.295
Skewness18.201513
Sum7769573.4
Variance98588918
MonotonicityNot monotonic
2024-01-26T10:27:54.785883image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8
 
0.3%
598.2 2
 
0.1%
589.15 2
 
0.1%
599.9 2
 
0.1%
306.55 2
 
0.1%
379.65 2
 
0.1%
178.96 2
 
0.1%
331 2
 
0.1%
1078.96 2
 
0.1%
2083.42 2
 
0.1%
Other values (2941) 2942
99.1%
ValueCountFrequency (%)
-796.86 1
 
< 0.1%
-141.48 1
 
< 0.1%
-95.93 1
 
< 0.1%
0 8
0.3%
5.684341886 × 10-141
 
< 0.1%
4.547473509 × 10-131
 
< 0.1%
12.24 1
 
< 0.1%
15 1
 
< 0.1%
36.56 1
 
< 0.1%
40.95 1
 
< 0.1%
ValueCountFrequency (%)
278778.02 1
< 0.1%
259657.3 1
< 0.1%
189735.53 1
< 0.1%
133007.13 1
< 0.1%
123638.18 1
< 0.1%
114505.32 1
< 0.1%
88138.2 1
< 0.1%
65920.12 1
< 0.1%
62924.1 1
< 0.1%
59419.34 1
< 0.1%

Interactions

2024-01-26T10:27:45.850408image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:14.898334image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:17.103152image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:19.566965image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:22.101652image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:24.447834image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:27.117276image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:29.536467image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:31.841267image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:34.280366image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:36.658670image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:39.111355image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:41.272307image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:43.627781image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:46.006825image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:15.047156image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:17.269438image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:19.731908image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:22.256620image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:24.626237image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:27.285874image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:29.695465image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:32.046236image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:34.440621image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:36.814409image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:39.264832image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:41.427769image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:43.785922image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:46.151104image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:15.207880image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:17.425554image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:19.911349image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:22.414102image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:25.083415image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:27.454558image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:29.863530image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:32.232867image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:34.611700image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:36.971952image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:39.407632image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:41.588540image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:43.938027image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:46.309460image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:15.369759image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:17.580146image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:20.080093image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:22.569300image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:25.254946image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:27.634634image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:30.028876image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:32.404192image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:34.779904image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:37.133390image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:39.575385image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:41.761997image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:44.100663image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:46.459761image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:15.512663image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:17.849172image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:20.230574image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:22.705028image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:25.411212image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:27.803554image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:30.179933image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:32.552030image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:34.928542image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:37.276240image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:39.709286image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:41.904239image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:44.249675image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:46.637319image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:15.682467image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:18.030992image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:20.424550image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:22.869697image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:25.593472image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:27.996350image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:30.351629image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:32.737613image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:35.110732image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:37.445367image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:39.882661image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:42.079731image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:44.420326image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:46.825227image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:15.850883image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:18.197124image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:20.651284image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:23.055456image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:25.780468image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:28.193996image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:30.536536image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:32.924798image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:35.311747image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:37.624386image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:40.044435image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:42.256070image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:44.612335image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:46.994555image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:16.023909image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:18.364949image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:20.827835image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:23.228145image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:25.947304image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:28.373790image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:30.698018image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:33.096895image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:35.497226image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:37.771462image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:40.203764image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:42.429007image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:44.771011image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:47.156664image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:16.179919image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:18.529320image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:21.019183image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:23.420849image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:26.129362image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:28.560014image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:30.865124image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:33.279335image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:35.667247image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:37.926973image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:40.362660image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:42.607351image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:44.931034image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:47.313326image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:16.344751image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:18.687579image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:21.224848image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:23.693805image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:26.305141image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:28.733338image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:31.031214image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:33.473572image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:35.841817image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:38.081792image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:40.533293image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:42.778751image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:45.102180image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:47.452272image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:16.488125image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:18.836204image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:21.388429image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:23.839413image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:26.463215image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:28.883399image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:31.180474image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:33.618803image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:35.997757image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:38.226382image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:40.679008image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:42.920930image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:45.247334image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:47.596976image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:16.629236image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:18.996512image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:21.592757image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:23.977330image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:26.621475image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:29.042183image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:31.342099image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:33.772041image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:36.146984image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:38.369483image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:40.818115image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:43.075989image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:45.395475image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:47.751384image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:16.793962image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:19.174452image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:21.769487image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:24.135660image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:26.785873image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:29.213425image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:31.514383image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:33.935314image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:36.327336image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:38.518814image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:40.970366image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:43.238593image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:45.549449image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:47.912565image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:16.950125image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:19.352972image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:21.945810image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:24.294132image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:26.947422image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:29.376439image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:31.678386image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:34.100059image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:36.494059image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:38.967947image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:41.123841image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:43.398948image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-26T10:27:45.702701image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Correlations

2024-01-26T10:27:54.940848image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketcustomer_iddelta_buy_returnfrequencygross_revenueitems_purchasedmonetary_returnsnumber_returnspurchasesrecency_daysunique_avg_basketunique_products_purchased
avg_basket_size1.000-0.0780.824-0.1230.5700.0280.5740.7290.1790.1780.101-0.0970.4490.384
avg_recency_days-0.0781.000-0.1140.019-0.237-0.881-0.249-0.228-0.399-0.422-0.2580.1090.049-0.165
avg_ticket0.824-0.1141.000-0.1420.6650.0570.6740.6210.2570.2440.107-0.0730.4270.376
customer_id-0.1230.019-0.1421.000-0.072-0.002-0.077-0.071-0.056-0.0490.0260.001-0.0070.013
delta_buy_return0.570-0.2370.665-0.0721.0000.0820.9940.9230.3300.3630.774-0.4190.2980.751
frequency0.028-0.8810.057-0.0020.0821.0000.0910.0810.2400.2360.0780.017-0.0730.035
gross_revenue0.574-0.2490.674-0.0770.9940.0911.0000.9250.3710.3910.772-0.4140.2920.746
items_purchased0.729-0.2280.621-0.0710.9230.0810.9251.0000.3250.3500.718-0.4070.3220.732
monetary_returns0.179-0.3990.257-0.0560.3300.2400.3710.3251.0000.9430.296-0.1180.0180.244
number_returns0.178-0.4220.244-0.0490.3630.2360.3910.3500.9431.0000.338-0.1430.0310.279
purchases0.101-0.2580.1070.0260.7740.0780.7720.7180.2960.3381.000-0.5030.0250.690
recency_days-0.0970.109-0.0730.001-0.4190.017-0.414-0.407-0.118-0.143-0.5031.000-0.108-0.436
unique_avg_basket0.4490.0490.427-0.0070.298-0.0730.2920.3220.0180.0310.025-0.1081.0000.699
unique_products_purchased0.384-0.1650.3760.0130.7510.0350.7460.7320.2440.2790.690-0.4360.6991.000

Missing values

2024-01-26T10:27:48.129200image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-26T10:27:48.468991image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_dayspurchasesunique_products_purchaseditems_purchasedavg_ticketavg_recency_daysfrequencynumber_returnsmonetary_returnsavg_basket_sizeunique_avg_basketdelta_buy_return
0178505391.21372.034.0297.01733.0158.56500035.50000017.0000001.0102.5850.9705888.7352945288.63
1130473232.5956.09.0171.01390.0359.17666727.2500000.0283027.0143.49154.44444419.0000003089.10
2125836705.382.015.0232.05028.0447.02533323.1875000.0403232.076.04335.20000015.4666676629.34
313748948.2595.05.028.0439.0189.65000092.6666670.0179210.00.0087.8000005.600000948.25
415100876.00333.03.03.080.0292.0000008.6000000.0731713.0240.9026.6666671.000000635.10
5152914623.3025.014.0102.02102.0330.23571423.2000000.0401155.071.79150.1428577.2857144551.51
6146885630.877.021.0327.03621.0268.13666718.3000000.0572216.0523.49172.42857115.5714295107.38
7178095411.9116.012.061.02057.0450.99250035.7000000.0335202.067.06171.4166675.0833335344.85
81531160767.900.091.02379.038194.0667.7791214.1444440.24331627.01348.56419.71428626.14285759419.34
9160982005.6387.07.067.0613.0286.51857147.6666670.0243900.00.0087.5714299.5714292005.63
customer_idgross_revenuerecency_dayspurchasesunique_products_purchaseditems_purchasedavg_ticketavg_recency_daysfrequencynumber_returnsmonetary_returnsavg_basket_sizeunique_avg_basketdelta_buy_return
5627177271060.2515.01.066.0645.01060.2500006.01.0000001.017.70645.00000066.01042.55
563717232421.522.02.036.0203.0210.76000012.00.1538460.00.00101.50000018.0421.52
563817468137.0010.02.05.0116.068.5000004.00.4000000.00.0058.0000002.5137.00
564913596697.045.02.0166.0406.0348.5200007.00.2500000.00.00203.00000083.0697.04
5655148931237.859.02.073.0799.0618.9250002.00.6666670.00.00399.50000036.51237.85
565912479473.2011.01.030.0382.0473.2000004.01.0000002.049.90382.00000030.0423.30
568014126706.137.03.015.0508.0235.3766673.00.7500001.062.50169.3333335.0643.63
5686135211092.391.03.0435.0733.0364.1300004.50.3000000.00.00244.333333145.01092.39
569615060301.848.04.0120.0262.075.4600001.02.0000000.00.0065.50000030.0301.84
571512558269.967.01.011.0196.0269.9600006.01.0000001.0269.96196.00000011.00.00